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@@ -213,6 +213,7 @@ def train(hyp, opt, device, tb_writer=None): |
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# Start training |
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t0 = time.time() |
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nw = max(3 * nb, 1e3) # number of warmup iterations, max(3 epochs, 1k iterations) |
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# nw = min(nw, (epochs - start_epoch) / 2 * nb) # limit warmup to < 1/2 of training |
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maps = np.zeros(nc) # mAP per class |
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results = (0, 0, 0, 0, 0, 0, 0) # 'P', 'R', 'mAP', 'F1', 'val GIoU', 'val Objectness', 'val Classification' |
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scheduler.last_epoch = start_epoch - 1 # do not move |
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@@ -477,8 +478,8 @@ if __name__ == '__main__': |
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'anchor_t': (1, 2.0, 8.0), # anchor-multiple threshold |
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'fl_gamma': (0, 0.0, 2.0), # focal loss gamma (efficientDet default gamma=1.5) |
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'hsv_h': (1, 0.0, 0.1), # image HSV-Hue augmentation (fraction) |
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'hsv_s': (1, 0.0, 0.8), # image HSV-Saturation augmentation (fraction) |
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'hsv_v': (1, 0.0, 0.8), # image HSV-Value augmentation (fraction) |
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'hsv_s': (1, 0.0, 0.9), # image HSV-Saturation augmentation (fraction) |
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'hsv_v': (1, 0.0, 0.9), # image HSV-Value augmentation (fraction) |
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'degrees': (1, 0.0, 45.0), # image rotation (+/- deg) |
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'translate': (1, 0.0, 0.9), # image translation (+/- fraction) |
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'scale': (1, 0.0, 0.9), # image scale (+/- gain) |
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@@ -495,7 +496,7 @@ if __name__ == '__main__': |
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if opt.bucket: |
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os.system('gsutil cp gs://%s/evolve.txt .' % opt.bucket) # download evolve.txt if exists |
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for _ in range(10): # generations to evolve |
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for _ in range(100): # generations to evolve |
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if os.path.exists('evolve.txt'): # if evolve.txt exists: select best hyps and mutate |
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# Select parent(s) |
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parent = 'single' # parent selection method: 'single' or 'weighted' |